Embedding Models

Embedding Models

Generates vector representations for text

All Features Documentation

Overview

Enables semantic search and retrieval

How It Works

Learn how Embedding Models integrates into your workflow, optimizes processes, and ensures reliability across your AI operations.

Key Benefits

Generates vector representations for text

Enables semantic search and retrieval

Use Cases

Retrieval-augmented generation (RAG)

Semantic similarity search in knowledge bases

Preguntas frecuentes

What are embedding models?

Models that convert text into numerical vectors for downstream tasks.

Why use embeddings?

They allow LLMs to understand and retrieve information based on meaning, not just keywords.

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